Recipient organisationPlant Ecology Beyond Land (pebl) CIC
Funding£92K
PeriodMar 2025 — Mar 2026
In plain English
AI plain-English summary
Floating offshore wind platforms in the Celtic Sea will soon have sonar systems listening for drifting nets and cables that could snare whales and dolphins. Unlike traditional fixed turbines, these floating platforms are anchored by mooring lines that hang through the water column, creating new entanglement risks for marine megafauna. The project will deploy imaging sonar along those lines in pool trials and at a test site near St. David's, then train machine-learning algorithms to identify debris size, shape, and type in near real-time. If successful, the system will push that analysis to edge devices on the turbines themselves, allowing immediate reporting of entanglement hazards without waiting for human review. The resulting evidence base would give regulators, conservation groups, and wind developers a concrete monitoring workflow, helping to consent future floating wind farms in the Celtic Sea while protecting the marine life that shares those waters. This is applied technology development with a clear practical endpoint: safer coexistence between renewable energy infrastructure and the animals that live around it.
View original technical description
This project focuses on addressing key environmental challenges associated with the deployment of floating offshore wind (FLOW) technology in South West Wales, a critical region for advancing renewable energy generation in the UK. FLOW offers a transformative opportunity to harness deeper water locations in the Celtic Sea, where up to 12 GW of additional energy capacity could contribute significantly to national net zero targets while driving economic growth in the region. Unlike traditional fixed offshore wind (OW) farms, FLOW operates in deeper waters (40m--1000m) using floating or semi-submersible platforms anchored by mooring lines and inter-array cables. However, these novel technologies introduce uncertainties regarding their environmental impacts, particularly risks of collision, entanglement, and marine debris entrapment that could cause secondary entanglement of marine megafauna such as cetaceans and large fish, as well as smaller marine species. Our project aims to develop and test cutting-edge monitoring technologies to address these challenges and facilitate the consenting process for future FLOW developments. In a proof-of-concept study, we will deploy imaging sonar systems along mooring lines in both controlled pool trials and at a marine test site near St. David's, South West Wales. The collected data will be analysed using artificial intelligence and machine learning (ML) techniques to identify and quantify entrapment events involving marine debris which could potentially lead to secondary entanglement of marine wildlife. Training datasets generated through these deployments will enable the development of algorithms capable of detecting the size, shape, and type of debris in near real-time. Additionally, we will explore the automated identification of marine megafauna, integrating acoustic data to enhance monitoring capabilities. We aim to push these ML processes to edge devices, enabling real-time incident reporting directly from turbine sites. This project will deliver a robust evidence base and monitoring workflow for regulatory bodies, conservation organisations, marine energy operators (MEOs) and FLOW developers, facilitating sustainable deployment in the Celtic Sea. The outcomes will support local innovation in environmental monitoring and foster collaboration within South West Wales' net zero industrial cluster, advancing regional expertise and global leadership in renewable energy innovation.
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